| | --- |
| | license: apache-2.0 |
| | base_model: indolem/indobertweet-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: gemash |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # gemash |
| |
|
| | This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.9414 |
| | - Accuracy: 0.8033 |
| | - Precision: 0.8149 |
| | - Recall: 0.8086 |
| | - F1: 0.8116 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0001 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 4 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 1.2534 | 1.0 | 169 | 0.9392 | 0.6333 | 0.6682 | 0.6642 | 0.6550 | |
| | | 0.6263 | 2.0 | 338 | 0.7132 | 0.7767 | 0.8099 | 0.7776 | 0.7901 | |
| | | 0.194 | 3.0 | 507 | 0.8639 | 0.7883 | 0.7911 | 0.8039 | 0.7961 | |
| | | 0.0485 | 4.0 | 676 | 0.9414 | 0.8033 | 0.8149 | 0.8086 | 0.8116 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
